Literature DB >> 9254982

Analysis of abnormal signals within the QRS complex of the high-resolution electrocardiogram.

P Gomis1, D L Jones, P Caminal, E J Berbari, P Lander.   

Abstract

This paper presents a new, quantitative approach to measuring abnormal intra-QRS signals, using the high-resolution electrocardiogram (HRECG). These signals are conventionally known as QRS "notches and slurs." They are measured qualitatively and form the basis for the ECG identification of myocardial infarction. The HRECG is used for detection of ventricular late potentials (LP), which are linked with the presence of a reentry substrate for ventricular tachycardia (VT) after a myocardial infarction. LP's are defined as signals from areas of delayed conduction which outlast the normal QRS period. Our objective is to quantify very low-level abnormal signals that may not outlast the normal QRS period. In this work, abnormal intra-QRS potentials (AIQP) were characterized by removing the predictable, smooth part of the QRS from the original waveform. This was represented as the impulse response of an ARX parametric model, with model order selected empirically from a training data set. AIQP were estimated using the residual of the modeling procedure. Critical AIQP parameters to separate VT and non-VT subjects were obtained using discriminant functions. Results suggest that AIQP indexes are a new predictive index of the HRECG for VT. The concept of abnormal intra-QRS potentials permits the characterization of pathophysiological signals contained wholly within the normal QRS period, but related to arrhythmogenesis. The new method may have other applications, such as detection of myocardial ischemia and improved ECG identification of the site of myocardial infarction, particularly in the absence of Q waves.

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Mesh:

Year:  1997        PMID: 9254982     DOI: 10.1109/10.605425

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

1.  Fragmentation of bandpass-filtered QRS-complex of patients prone to malignant arrhythmia.

Authors:  P Endt; H D Hahlbohm; D Kreiseler; M Oeff; U Steinhoff; L Trahms
Journal:  Med Biol Eng Comput       Date:  1998-11       Impact factor: 2.602

2.  Analysis of speed, curvature, planarity and frequency characteristics of heart vector movement to evaluate the electrophysiological substrate associated with ventricular tachycardia.

Authors:  Larisa G Tereshchenko; Jonathan W Waks; Muammar Kabir; Elyar Ghafoori; Alexei Shvilkin; Mark E Josephson
Journal:  Comput Biol Med       Date:  2015-03-19       Impact factor: 4.589

3.  Automatic optimum order selection of parametric modelling for the evaluation of abnormal intra-QRS signals in signal-averaged electrocardiograms.

Authors:  C C Lin; C M Chen; I F Yang; T F Yang
Journal:  Med Biol Eng Comput       Date:  2005-03       Impact factor: 2.602

4.  Identification of post-myocardial infarction patients with ventricular tachycardia by time-domain intra-QRS analysis of signal-averaged electrocardiogram and magnetocardiogram.

Authors:  P Endt; J Montonen; M Mäkijärvi; J Nenonen; U Steinhoff; L Trahms; T Katila
Journal:  Med Biol Eng Comput       Date:  2000-11       Impact factor: 2.602

5.  Heart detection and diagnosis based on ECG and EPCG relationships.

Authors:  W Phanphaisarn; A Roeksabutr; P Wardkein; J Koseeyaporn; Pp Yupapin
Journal:  Med Devices (Auckl)       Date:  2011-08-26

6.  Analysis of Abnormal Intra-QRS Potentials in Signal-Averaged Electrocardiograms Using a Radial Basis Function Neural Network.

Authors:  Chun-Cheng Lin
Journal:  Sensors (Basel)       Date:  2016-09-27       Impact factor: 3.576

  6 in total

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